First Advisor

Xiaoyu Song

Term of Graduation

Spring 2020

Date of Publication

6-9-2020

Document Type

Dissertation

Degree Name

Doctor of Philosophy (Ph.D.) in Electrical and Computer Engineering

Department

Electrical and Computer Engineering

Language

English

Subjects

Quantum computing

DOI

10.15760/etd.7324

Physical Description

1 online resource (xv, 120 pages)

Abstract

Large-scale quantum computers can solve certain problems that are not tractable by currently available classical computational resources. The building blocks of quantum computers are qubits. Among many different physical realizations for qubits, superconducting qubits are one of the promising candidates to realize gate model quantum computers. In this dissertation, we present new multi-qubit gates for nearest-neighbor superconducting quantum systems. In the absence of a physical hardware, we simulate the dynamics of the quantum system and use the simulated environment as a framework for test, design, and optimization of quantum gates and architectures. We explore three different simulation-based gate design methodologies: analytical approach, heuristic method, and machine learning techniques. Furthermore, we propose novel quantum error correction architectures utilizing our new gates, which have reduced computational overhead with better performance and reliability.

Rights

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Persistent Identifier

https://archives.pdx.edu/ds/psu/33236

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